Pricing and power control for energy-efficient radio resource management in cognitive femtocell networks

Cognitive femtocell has been considered as a promising technique that can improve the capacity and the utilization of spectrum efficiency in wireless networks because of the short transmission distance and low transmit power. In this paper, we study the win-win solution of energy-efficient radio resource management in cognitive femtocell networks, where the macrocell tries to maximize its revenue by adjusting spectrum utilization price while the femtocells try to maximize their revenues by dynamically adjusting the transmit power. When the spectrum utilization price is given by macrocell, we formulate the power control problem of standalone femtocells as an optimization problem and introduce a low-complexity iteration algorithm based on gradient-assisted binary search algorithm to solve it. Besides, non-cooperative game is used to formulate the power control problem between collocated femtocells in a collocated femtocell set, and then low complexity and widely used gradient-based iteration algorithm is applied to obtain the Nash-equilibrium solution. Specially, asymptotic analysis is applied to find the approximate spectrum utilization price in macrocell, which can greatly reduce the computational complexity of the proposed energy-efficient radio resource management scheme. Finally, extensive simulation results are presented to verify our theoretical analysis and demonstrate the performance of the proposed scheme. Copyright (c) 2013 John Wiley & Sons, Ltd.